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@INPROCEEDINGS{Tweddell:828241,
      author       = {Tweddell, Bastian and Göbbert, Jens Henrik and Gauding,
                      Michael and Weyers, Benjamin and Hagemeier, Björn},
      title        = {{F}ramework for {S}haring of {H}ighly {R}esolved
                      {T}urbulence {S}imulation {D}ata},
      volume       = {10164},
      address      = {Cham},
      publisher    = {Springer International Publishing},
      reportid     = {FZJ-2017-02209},
      isbn         = {978-3-319-53861-7 (print)},
      series       = {Lecture Notes in Computer Science},
      pages        = {225 - 232},
      year         = {2017},
      comment      = {High-Performance Scientific Computing / Di Napoli, Edoardo
                      (Editor) ; Cham : Springer International Publishing, 2017,
                      Chapter 19 ; ISSN: 0302-9743=1611-3349 ; ISBN:
                      978-3-319-53861-7=978-3-319-53862-4 ;
                      doi:10.1007/978-3-319-53862-4},
      booktitle     = {High-Performance Scientific Computing
                       / Di Napoli, Edoardo (Editor) ; Cham :
                       Springer International Publishing,
                       2017, Chapter 19 ; ISSN:
                       0302-9743=1611-3349 ; ISBN:
                       978-3-319-53861-7=978-3-319-53862-4 ;
                       doi:10.1007/978-3-319-53862-4},
      abstract     = {The growing computational capabilities of nowadays
                      super-computers have made highly resolved turbulence
                      simulations possible.The large data-sets and tremendous
                      amount of required compute re-sources create serious new
                      challenges when attempting to share the databetween
                      different research groups. But even more difficult to solve
                      isthe incompatibility of the data formats and numerical
                      approaches usedfor turbulence simulations. In this paper a
                      framework for sharing dataof large scale simulations is
                      presented, which simplifies the access andfurther
                      post-processing even beyond a single supercomputing center.
                      Itcombines established services to provide an easy to
                      manage-and-extendsoftware setup without the need to
                      standardize a database or -format.},
      month         = {Oct},
      date          = {2016-10-04},
      organization  = {JARA-HPC Symposium 2016, Aachen
                       (Germany), 4 Oct 2016 - 5 Oct 2016},
      cin          = {JSC / JARA-HPC},
      ddc          = {004},
      cid          = {I:(DE-Juel1)JSC-20090406 / $I:(DE-82)080012_20140620$},
      pnm          = {511 - Computational Science and Mathematical Methods
                      (POF3-511) / 512 - Data-Intensive Science and Federated
                      Computing (POF3-512) / 513 - Supercomputer Facility
                      (POF3-513)},
      pid          = {G:(DE-HGF)POF3-511 / G:(DE-HGF)POF3-512 /
                      G:(DE-HGF)POF3-513},
      typ          = {PUB:(DE-HGF)8 / PUB:(DE-HGF)7},
      doi          = {10.1007/978-3-319-53862-4_19},
      url          = {https://juser.fz-juelich.de/record/828241},
}